Research On The Key Problems Of Formation Of UAV

With the development of society,UAV has been widely used in military and civil fields due to its advantages of high performance,low cost and strong environmental adaptability.Unmanned aerial vehicles(UAV),which do not require human pilots to fly,have gradually replaced human aircraft in many fields.Among them,UAV flight path planning is the primary problem to be solved in the practical application of UAV.The planning of a single mission point can no longer meet the requirements of multi-mission scenarios,so the research on UAV multi-mission point flight path planning arises at the right moment.However,in practice,because most tasks are concurrent and comprehensive,a single UAV can no longer be completed independently,so the research on UAV formation system is increasing.Therefore,this paper focuses on the problems of UAV single mission point flight path planning,multi-mission point flight path planning and UAV formation flight.Firstly,a path planning method based on artificial potential field algorithm(APF)and fast random extension tree algorithm(RRT)is proposed.By introducing the idea of target gravity,the problem of low search efficiency of traditional random extended tree algorithm is improved.At the same time,the greedy strategy is introduced to remove redundant nodes,and the transition trajectory generation strategy is added to smooth the path corner.This improves the speed and quality of planning.Finally,the simulation results show that under the same flight environment,the flight path planning time is reduced by about 56.2%,the flight path length is shortened by about 25%,and the number of uav turns is reduced,so the loss of UAV is reduced.Secondly,by analyzing the problems encountered in the application of traditional particle swarm optimization(PSO)in path planning,a path planning method for UAV based on improved potential field particle swarm optimization(PSO)is proposed.By introducing the artificial potential field algorithm into the updating formula of particle velocity and position,the defects of the standard traditional particle swarm optimization(PSO)algorithm are improved,and the feasibility and effectiveness of the proposed algorithm are verified in the simple and complex simulation environment.Thirdly,a multi-task point path planning method based on parallel particle swarm optimization(PSO)is proposed.Firstly,the safe distance between any two target points is calculated by the adaptive elite-particle swarm optimization algorithm and the corresponding safe distance matrix is formed.Secondly,the particle swarm optimization(PSO)algorithm is used to find the optimal order according to the safe distance matrix.Finally,according to the optimal order,the multi-objective path planning is realized.The concept of parallel computation is introduced to improve the running efficiency of the algorithm.Simulation results show that the algorithm is feasible and effective.Finally,the research of single aircraft control and formation flight control is carried out for the four-rotor UAV.First for single UAV control using PID and sliding mode control for the design of the controller,through the MATLB simulation platform,the simulation analysis of controller performance,followed by using the algorithm,realizes the unmanned aerial vehicle formation flight,and on the MATLAB simulation platform,the design of circular trajectory tracking experiment,implementation of the circular trajectory linear formation flight,and the formation controller is used to generate the circular formation and to keep the formation in translation.